the nih collaboratory distributed research network · 05/06/2015 · the goal the nih...
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The NIH CollaboratoryDistributed Research Network
Jeffrey BrownHarvard Pilgrim Health Care Institute and
Harvard Medical School
June 5, 2015
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The Goal
The NIH Collaboratory DRN facilitates research partnerships with organizations (Data Partners) that possess electronic health data that have been quality checked and formattedto support multi-site biomedical research
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https://www.nihcollaboratory.org/Pages/distributed-research-network.aspx
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• Provide information to support research planning
• Background rates
• Assess assumptions about relevant populations
• Prioritize research domains
• Answer specific research questions
• Identify sites for participation in prospective interventional or observational studies
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Uses of the Distributed Network
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• Research ready data sets representing >90% of the FDA Sentinel program
• > 300 million person-years of observation time and detailed information for billions of medical encounters and outpatient pharmacy dispensings
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Currently Available Data
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Unique Individuals by Age Range
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Data Elements
• Captured
• Ambulatory care diagnoses and procedures
• Outpatient pharmacy dispensing
• Laboratory testing and selected test results
• Inpatient diagnoses, treatments and procedures itemized in hospital bill
• Not captured
• Out of hospital death
• Over-the-counter medication
• Community-based immunizations
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Data Model
Some data partners do not create every table (e.g., vital signs are available for only a subset of individuals)
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The Easy –Hard Continuum of Questions
• Easy: Can be answered with existing programs• Counts, exposure-outcome relationships, confounder adjusted
comparative cohort analyses
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The Easy –Hard Continuum of Questions
• Easy: Can be answered with existing programs• Counts, exposure-outcome relationships, confounder adjusted
comparative cohort analyses
• Moderate: Can be answered with new programming• Data exists, is well characterized, and known to be reliable
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The Easy –Hard Continuum of Questions
• Easy: Can be answered with existing programs• Counts, exposure-outcome relationships, confounder adjusted
comparative cohort analyses
• Moderate: Can be answered with new programming• Data exists, is well characterized, and known to be reliable
• Hard: Requires investigation or mapping of existing data• Data exists but completeness and quality must be determined
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The Easy –Hard Continuum of Questions
• Easy: Can be answered with existing programs• Counts, exposure-outcome relationships, confounder adjusted
comparative cohort analyses
• Moderate: Can be answered with new programming• Data exists, is well characterized, and known to be reliable
• Hard: Requires investigation or mapping of existing data• Data exists but completeness and quality must be determined
• Harder: New data is needed• Birth registry, death registry, etc
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The Easy –Hard Continuum of Questions
• Easy: Can be answered with existing programs• Counts, exposure-outcome relationships, confounder adjusted
comparative cohort analyses
• Moderate: Can be answered with new programming• Data exists, is well characterized, and known to be reliable
• Hard: Requires investigation or mapping of existing data• Data exists but completeness and quality must be determined
• Harder: New data is needed• Birth registry, death registry, etc
• Impossible: The data isn’t reliably captured • Race, smoking status, over the counter medication use
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Where does the question fall on the continuum
• The DRN Coordinating Center helps requesters or their designees understand and use the network
• Assess fit between requests and the DRN’s capabilities
• Suggest ways to maximize usefulness of the DRN data resources
• Facilitate engagement with data partners
• Requesters do not have to be experts in observational research or use of health care data to initiate a request
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Easy Example: Simple Counts
• Query goals
• Counts of patients with Progressive Multifocal
Leukoencephalopathy (PML)
• Analysis
• Number of patients and prevalence rate of PML
identified in inpatient setting
• Counts provided per patient per year, age group, and sex
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Result: In 2012, there were 87 individuals identified
•Prevalence of Progressive Multifocal Leukoencephalopathy
in 2012
Age
(years)
Males Prevalence
per 10,000
Females Prevalence per
10,000
0-21 1 0.01 0 0
22-44 16 0.14 8 0.07
45-64 29 0.31 18 0.18
65+ 6 0.16 9 0.20
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Easy Example: Simple Counts
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Easy Example: Cohort Identification and Descriptive Analysis• Query goals• Patients continuously exposed to bisphosphonates for >3 years
• Assess the risk of hip and other fractures
• Analysis• 2006 - 2013
• Health plan members with medical and pharmacy coverage
• New users of alendronate, risedronate, & ibandronate
• Create treatment episodes based on repeated exposures
• Identify fractures during or shortly after treatment
• Sensitivity analyses examined different exposure, event, and episode definitions (n=78 analyses)
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Results• ~34,000 new users
• ~22,000 current alendronate users exposed for 3 - 5 years
• ~9,000 people enter this cohort each year
Fractures in long term alendronate users*
Fracture typeExposed
people
Person
time (yrs)Fractures
Rate /
10K yrs
Hip 34,428 138,386 725 52
Femoral
fractures of
interest
34,672 140,020 339 24
* New users of alendronate, continuously exposed for at least 3 years
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Easy Example: Cohort Identification and Descriptive Analysis
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www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdf
• Query goals• What is the comparative risk of angioedema
among new users of ACE inhibitors vs. new users of beta-blockers?
• Analysis• Propensity score matched survival analysis
• Performed via reusable modular program requiring only specification of input parameters
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Easy Example: Propensity score matched comparison
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Input parameters• Population (age/sex/etc.), time period• Exposures• Outcomes
• ICD-9-CM code 995.1 in any position during outpatient, inpatient, or emergency department encounter
• Washout period (days before first dispensing): 183 days
• Inclusion criteria• Exclusion criteria• Covariates• Propensity score matching options
• Comorbidity, utilization, high dimensional propensity score• Matching ratio• Caliper size
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Easy Example: Propensity score matched comparison
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Angioedema: Table 1. Unmatched Cohort
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdf
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Angioedema: Table 1. Unmatched Cohort
3.9 million new users
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdf
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Angioedema: Table 1. Unmatched Cohort
3.9 million new users
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdf
Diabetes 21% vs 10%Heart failure 2% vs 4%Ischemic heart disease 5% vs 13%
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Propensity Scores Before Match
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdfDP3
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Angioedema: Table 2. Matched Cohort
2.6 million new users
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdf
Diabetes 10% vs 10%Heart failure 3% vs 3%Ischemic heart disease 8% vs 8%
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Propensity Scores After Match
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdfDP3
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Angioedema: Table 3. Results
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdf
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Angioedema: Table 3. Results
ACEI vs β-blocker 1:1 matched analysis:• HR = 3.1
(95% CI, 2.9-3.4)
www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Known-Positives-ACEI-Angioedema.pdf
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• Plan to replicate the TACT trial – EDTA chelation to prevent coronary heart disease – focusing on diabetic patients
• Inclusion criteria
• > 50 years old
• Confirmed diagnosis of diabetes on medical therapy (insulin or oral)
• Previous myocardial infarction
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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• Plan to replicate the TACT trial – EDTA chelation to prevent coronary heart disease – focusing on diabetic patients
• Inclusion criteria
• > 50 years old
• Confirmed diagnosis of diabetes on medical therapy (insulin or oral)
• Previous myocardial infarction
EASY: All inclusion criteria are available for querying using existing cohort identification programs
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
• EASY: Available for a subset; >7million results available
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
• EASY: Available for a subset; >7million results available
• Cigarette smoking within 3 months
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
• EASY: Available for a subset; >7million results available
• Cigarette smoking within 3 months
• IMPOSSIBLE: Smoking status not recorded in claims and unreliable in EHRs
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
• EASY: Available for a subset; >7million results available
• Cigarette smoking within 3 months
• IMPOSSIBLE: Smoking status not recorded in claims and unreliable in EHRs
• Heart failure or heart failure hospitalization
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
• EASY: Available for a subset; >7million results available
• Cigarette smoking within 3 months
• IMPOSSIBLE: Smoking status not recorded in claims and unreliable in EHRs
• Heart failure or heart failure hospitalization
• EASY: Available
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
• EASY: Available for a subset; >7million results available
• Cigarette smoking within 3 months
• IMPOSSIBLE: Smoking status not recorded in claims and unreliable in EHRs
• Heart failure or heart failure hospitalization
• EASY: Available
• No chelation therapy in prior 5 years
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
Exclusion criteria
• Creatinine > 2.0 mg/dl
• EASY: Available for a subset; >7million results available
• Cigarette smoking within 3 months
• IMPOSSIBLE: Smoking status not recorded in claims and unreliable in EHRs
• Heart failure or heart failure hospitalization
• EASY: Available
• No chelation therapy in prior 5 years
• Probably EASY: Need to assess data capture reliability and payment policies
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• Question: What are the demographic characteristics of patients that might be eligible – race, gender, age? What about comorbidities?
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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• Question: What are the demographic characteristics of patients that might be eligible – race, gender, age? What about comorbidities?
• EASY: Age, sex, and comorbidities can be defined and presented
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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• Question: What are the demographic characteristics of patients that might be eligible – race, gender, age? What about comorbidities?
• EASY: Age, sex, and comorbidities can be defined and presented
• IMPOSSIBLE: Race is recorded for a subset of patients
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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• Question: What can you tell us about where patients who meet these criteria receive most of their care – primary care offices, cardiology offices, endocrinology clinics? Does this vary in urban, suburban, more rural communities?
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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• Question: What can you tell us about where patients who meet these criteria receive most of their care – primary care offices, cardiology offices, endocrinology clinics? Does this vary in urban, suburban, more rural communities?
• HARD: Facility and provider codes are available; new programming and discussion with data partners would be required
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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• What can you tell us about the uncertainties in these estimates?
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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• What can you tell us about the uncertainties in these estimates?
• Suggest using sensitivity analyses to assess importance of each definition
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Example Request AssessmentTrial to Assess Chelation Therapy (TACT) Replication
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Request: Characterize rate of follow-up of abnormal cancer screening tests, including mammography, fecal immunochemical (FIT), or Pap tests within a managed care population
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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• Identification of benefit design – to define “managed care” – is possible but complex
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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• Identification of benefit design – to define “managed care” – is possible but complex
• Assessment of complexity and validity over time is needed
• Definition of “managed care”
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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1. How many are screened for each cancer?
2. How many have abnormal screening test results?
3. How many abnormal results appear to have no further testing?
a. For mammography – no additional mammography, ultrasound, MRI or biopsy with 90 days
b. For FIT – no colonoscopy within 90 days
c. For PAP – no repeat PAP that is normal, or no colposcopy within 90 days
4. Is there other evidence of evaluation of the abnormality?
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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1. How many are screened for each cancer?
2. How many have abnormal screening test results?
3. How many abnormal results appear to have no further testing?
a. For mammography – no additional mammography, ultrasound, MRI or biopsy with 90 days
b. For FIT – no colonoscopy within 90 days
c. For PAP – no repeat PAP that is normal, or no colposcopy within 90 days
4. Is there other evidence of evaluation of the abnormality?
EASY: Questions 1-4 can be answered using existing data and programs
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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5. Does the rate of follow up of abnormal test results vary across practices?
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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5. Does the rate of follow up of abnormal test results vary across practices?
HARD: Facility and provider codes are available; new programming and discussion with data partners would be required
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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5. Does the rate of follow up of abnormal test results vary across practices?
HARD: Facility and provider codes are available; new programming and discussion with data partners would be required
What are the race and age breakdowns of patients?
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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5. Does the rate of follow up of abnormal test results vary across practices?
HARD: Facility and provider codes are available; new programming and discussion with data partners would be required
What are the race and age breakdowns of patients?
• EASY: Age distribution
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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5. Does the rate of follow up of abnormal test results vary across practices?
HARD: Facility and provider codes are available; new programming and discussion with data partners would be required
What are the race and age breakdowns of patients?
• EASY: Age distribution
• IMPOSSIBLE: Race
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Example Request AssessmentFollow Up of Abnormal Cancer Screening Tests
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• Data Partners participate on a project-by-project-basis
• Submit requests using the NIH Collaboratory DRN request form
• The DRN Coordinating Center reviews each request to assess
appropriateness and level of effort
• Costs: on a case-by-case basis
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How to Use the NIH CollaboratoryDistributed Research Network
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https://www.nihcollaboratory.org/Pages/distributed-research-network.aspx
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Thank you!